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A research-to-reproducibility library. Articles are written with a "code angle" first: concrete steps to implement, reproduce, and extend.

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Introduction to Spiking Neural Networks

Learn how spiking neural networks mimic real brain computation with discrete spikes instead of continuous values.

Hebbian Learning and Synaptic Plasticity

Discover how neurons that fire together wire together - the foundational principle behind learning and memory in biological and artificial systems.

The Leaky Integrate-and-Fire Neuron Model

Master the LIF neuron model - the workhorse of computational neuroscience that balances biological realism with mathematical tractability.

Neural Coding: Rate vs Temporal Coding

Explore how the brain encodes information - through firing rates, precise spike timing, or both. The answer shapes our understanding of neural computation.

Neuromorphic Computing Hardware: Building Brains in Silicon

Explore the chips designed to compute like brains - from Intel Loihi to IBM NorthPole. Learn why neuromorphic hardware could revolutionize AI efficiency.

Welcome: From Brain to Code

What this project is building, and how to use the simulators + pipeline.